Author: Fu, Jianglin
Beamforming is a technique which can adaptively steer the pattern of a microphone array towards or away from a target direction. Three conventional beamforming techniques are reviewed and compared with a beamformer proposed here, called MVDR-2C. Most acoustic beamformers selectively locate a single desired sound source, such as a speaker, and the beamforming performance drops significantly when two or more speakers are active. In order to deploy beamforming in a room, a circular microphone array is supplemented by a 360° camera comprising two fisheye lenses. The camera allows face detection to provide the speaker directions to the beamformer. In order to develop face/object detectors that operate directly on fisheye images, three annotated fisheye datasets are generated and used to re-train an existing face detector. Finally, several beamformers are evaluated and compared, demonstrating the clear performance advantage of the proposed one.
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Thesis advisor: bajic, ivan
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